Driehorst, T. | Search bioRxiv

bioRxiv2025

SarcAsM: AI-based multiscale analysis of sarcomere organization and contractility in cardiomyocytes

Cardiomyocyte function critically depends on sarcomere dynamics and their organization in myofibrils. To uncover how cardiomyocyte function emerges from individual sarcomere dynamics, comprehensive analysis of Z-bands (nanometer scale), sarcomeres ([~]2 {micro}m scale), and myofibrils ([~]10 to 100 {micro}m scale) is required. Tools for such multiscale analyses are presently lacking. Here we introduce the Sarcomere Analysis Multitool (SarcAsM), which combines deep learning and graph-based methods for automated, fast, and unbiased structural assessment of sarcomeric Z-bands, sarcomeres, and myofibrils as well as their organization in larger myofibril domains. SarcAsM features a generalist deep learning model, pre-trained on a broad range of experimental and published images, ensuring its versatile application and immediate usability across diverse datasets. Finally, we demonstrate the versatile utility of SarcAsM in analyzing sarcomere structure and dynamics under acute and chronic drug exposure in hiPSC-derived cardiomyocytes with fluorescently tagged Z-bands. SarcAsM is available as open-source Python package and stand-alone application.

bioinformatics↗

bioRxiv2024

Stochastic tug-of-war among sarcomeres mediates cardiomyocyte response to environmental stiffness

Cardiac contraction is driven by the collective action of cardiomyocytes, that contain parallel bundles of myofibrils consisting of linear chains of sarcomeres, the basic force-generating units. The dynamics of individual sarcomeres within intact cardiomyocytes remain incompletely understood. While most models assume uniform, synchronized contractions, recent studies hint at unexpected heterogeneity whose origins and significance are not yet clear. By combining the culture of fluorescent sarcomere-reporter hiPSC-derived cardiomyocytes on micropatterned soft gels of different stiffness (5 - 85 kPa) with AI-based tracking of sarcomere motion, we found that increasingly stiff substrates inhibited overall cardiomyocyte contraction, but, surprisingly, did not diminish individual sarcomere dynamics. Instead, sarcomeres competed in a tug-of-war causing increasing heterogeneity, including rapid length oscillations and overextensions (popping). Statistical analysis showed that the heterogeneous dynamics were not caused by static structural differences but were largely stochastic. Stochastic heterogeneity is thus an intrinsic property of cardiac sarcomeres and likely mediates the adaptation of cardiomyocyte contractility to mechanical constraints. A mesoscopic model of coupled sarcomeres shows that these phenomena can be explained by a non-monotonic force-velocity relationship and stochastic fluctuations, where dynamic instability at a critical yielding force creates heterogeneity. Stochastic heterogeneity compensates for structural disorder by randomizing yield events beat-to-beat, preventing damage to specific sarcomeres. Our findings recast cardiac sarcomeres as active, dynamically unstable, and stochastic units engaged in a stochastic tug-of-war, where transient, velocity-dependent forces dominate. We propose that pathological disorder in cardiomyopathy drives a transition from protective stochastic fluctuations to more deterministic, persistently overloaded sarcomeres.

biophysics↗